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Improving Air-Conditioner and Heat Pump Modeling

Building America Stakeholders Meeting

Jon Winkler

March 2, 2012 NREL/PR-5500-54361

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• How do you recommend the most cost-effective A/C?

Simple Question

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Solution Whole-House Simulation Tool

A/C Information • SEER 13 • SEER 14 • SEER 15 • SEER 16

• SEER 17 • SEER 18 • SEER 21

Annu

aliz

ed C

oolin

g Cos

t (E

nerg

y + Eq

uipm

ent)

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Background

• Power, capacity and SHR vary with: o Outdoor temperature o Entering wetbulb o Air mass flow rate o Part load ratio

Power

SensibleCapacity

LatentCapacity

• How to accurately and easily model A/C performance?

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Background: Model Development

• A/C modeling utilizes two types of input o Rated values (capacity, efficiency, etc.) o Performance curves

Capacity 1 / Efficiency

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Background: Manufacturer’s Data

Simulation study: • 5 leading manufacturers (76% of the market) • 450+ air-conditioners and heat pumps • SEER 13 – 21

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Houston: 2,500 ft2 IECC 2009

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3

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SEER 13 SEER 16 SEER 15 SEER 14 SEER 21 SEER 18 SEER 17

Avg.

Ann

ual C

OP n

et,s

s

?

Results: Specific A/C Units

( )

( )∑

∑

=

=

+

−= 8760

1

8760

1,

nblowercompressor

nblowerDX

ssnet

PP

PQCOP

?

?

Tons1.5 2 2.5 3 3.5 4 5

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Results: Specific A/C Units

Houston: 2,500 ft2 IECC 2009

2

3

4

5

6

7

SEER 13 SEER 16 SEER 15 SEER 14 SEER 21 SEER 18 SEER 17

Avg.

Ann

ual C

OP n

et,s

s

?

?

? ?

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Results: Specific A/C Units

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3

4

5

6

7

SEER 13 SEER 16 SEER 15 SEER 14 SEER 21 SEER 18 SEER 17

Avg.

Ann

ual C

OP n

et,s

s

?

?

? ?

Question #1: What leads to the variation in average annual COP?

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Sensitivity to Curve Inputs

• Simulation inputs o Rated values (capacity, efficiency, etc.) o Performance curves

• Which type of input is leading to the observed variation? o What happens if a selected set of curves are used

for all simulations?

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2

3

4

5

6

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SEER 13 SEER 16 SEER 15 SEER 14 SEER 21 SEER 18 SEER 17

Avg.

Ann

ual C

OP n

et,s

s Results: Sensitivity to Curve Inputs

Conclusion #1: Annual simulation results are not highly dependent on the selected performance curves

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Results: Specific A/C Units

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3

4

5

6

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SEER 13 SEER 16 SEER 15 SEER 14 SEER 21 SEER 18 SEER 17

Avg.

Ann

ual C

OP n

et,s

s

? ?

Question #2: Does the efficiency of high SEER A/C’s decrease for higher tonnage units?

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Results: SEER vs. Tonnage

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14

15

16

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18

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21

22

SEER

"SEER 18" "SEER 21"

Certified AHRI Data

Conclusion #2: SEER is highly effected by nominal tonnage for high efficiency equipment

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Results: Specific A/C Units

2

3

4

5

6

7

SEER 13 SEER 16 SEER 15 SEER 14 SEER 21 SEER 18 SEER 17

Avg.

Ann

ual C

OP n

et,s

s

Question #3: How do we generalize A/C energy use across different SEER levels?

?

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Results: Standardized Set of A/C Options

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3

4

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6

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SEER 13 SEER 16 SEER 15 SEER 14 SEER 21 SEER 18 SEER 17

Avg.

Ann

ual C

OP n

et,s

s

Conclusion #3: Develop a set of rated performance inputs for generic A/C units to be consistent across SEER levels

Standardized Set of A/C Options

Individual A/C products can still be modeled using specific performance ratings as inputs

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Conclusions

When comparing different A/C’s: 1. Specific performance curves don’t really

matter 2. Be careful of “Up to SEER…” 3. The rated performance data does matter

and needs to be consistent

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Application: BEopt – Simplified Inputs

• Benefits o Easily model specific make & model A/C’s o Negligible sacrifice in accuracy/flexibility

BEopt 1.1 Cooling EER 12.72 COOL_CAP_FT_SPEC_coefficients 1.61196622,-0.03412895,0.00044551,0.00278667,-0.00000211,-0.00008969 COOL_SH_FT_SPEC_coefficients 0.42251614,0.07360185,-0.00089453,-0.00840292,0.00001615,0.00004937 COIL_BF_FT_SPEC_coefficients 56.67437760,-1.66560721,0.01245741,0.0,0.0,0.0 COOL_EIR_FT_SPEC_coefficients -0.68032067,0.03410170,-0.00025020,0.00559185,0.00010461,-0.00015031 COOL_EIR_FPLR_SPEC_coefficients 0.00000728,1.09852231,-0.11487027,0.01634067 COOL_CLOSS_FPLR_SPEC_coefficients 0.90949556,0.09864773,-0.00819488 COIL_BF_FFLOW_SPEC_Max 1.0 COIL_BF_FFLOW_SPEC_Min 0.0 COIL_BF_FFLOW_SPEC_coefficients 1.0, 0.0 FAN_EIR_FPLR_SPEC_coefficients 0.0, 1.0, 0.0, 0.0 SupplyKW 0.000256 CoilBF 0.100700

BEopt 1.2 Cooling SEER 14.0 Cooling EER 11.98 SHR 0.74 SupplyFanPower 0.365

User inputs for single stage units

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Application: BEopt – Consistent Results

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Application: BEopt – Consistent Results

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Tota

l Coo

ling

Sour

ce E

nerg

y (M

Btu/

yr)

BEoptE+ Parametric Simulation

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Building America Gaps and Barriers

• Gap: Analysis Methods and Tools Standing Technical Committee o BA Strategic Plans: http://www1.eere.energy.gov/buildings/building_america/strategic_plan.html

• Achievements o “… it is important to continually update and advance air-

conditioner and heat pump modeling approaches and capabilities.”

o “Additionally, it is important that users can easily enter specific air-conditioners into building simulation software (such as BEopt) in order to compare specific manufactured units not included in built-in component libraries.”

Thanks! Jon Winkler jon.winkler@nrel.gov 303.275.4356